class_docstr: Classifier based on BERT implementation.
code: def __init__(self, opt, shared=None):
      # download pretrained models
      download(opt["datapath"])
      self.pretrained_path = PathManager.get_local_path(
          os.path.join(
              opt["datapath"], "models", "bert_models", MODEL_PATH
          )
      )
      opt["pretrained_path"] = self.pretrained_path
      self.add_cls_token = opt.get("add_cls_token", True)
      self.sep_last_utt = opt.get("sep_last_utt", False)
      self.classifier_layers = opt.get("classifier_layers", None)
      super().__init__(opt, shared)
  
imports: import os
  from collections import deque
  from typing import Optional
  import torch
  from parlai.agents.bert_ranker.bert_dictionary import BertDictionaryAgent
  from parlai.agents.bert_ranker.helpers import BertWrapper, MODEL_PATH
  from parlai.core.opt import Opt
  from parlai.core.params import ParlaiParser
  from parlai.core.torch_agent import History
  from parlai.core.torch_classifier_agent import TorchClassifierAgent
  from parlai.utils.io import PathManager
  from parlai.utils.misc import warn_once
  from parlai.zoo.bert.build import download
label_desc: Use image node_id 1 to create a new BertClassifierAgent object from inherited base classes: TorchClassifierAgent with example: obj = BertClassifierAgent(opt, shared)